A Multiagent Evolutionary Algorithm for the Resource-Constrained Project Portfolio Selection and Scheduling Problem

被引：12
|
作者：
Shou, Yongyi [1 ]
Xiang, Wenwen [1 ]
Li, Ying [1 ]
Yao, Weijian [1 ]
机构：
[1] Zhejiang Univ, Sch Management, Hangzhou 310058, Zhejiang, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2014年 / 2014卷
基金：
中国国家自然科学基金;
关键词：
GENETIC ALGORITHM; ALLOCATION; OPTIMIZATION;
D O I：
10.1155/2014/302684
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent's energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resourceconstrained project portfolio selection and scheduling problem.
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收藏
页数：9
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